This documentation is about Terracotta DSO, an advanced distributed-computing technology aimed at meeting special clustering requirements.

Terracotta products without the overhead and complexity of DSO meet the needs of almost all use cases and clustering requirements. To learn how to migrate from Terracotta DSO to standard Terracotta products, see Migrating From Terracotta DSO. To find documentation on non-DSO (standard) Terracotta products, see Terracotta Documentation. Terracotta release information, such as release notes and platform compatibility, is found in Product Information.

Terracotta Cache Evictor

Introduction

The Terracotta Cache Evictor is an interface providing a simple distributed eviction solution for map elements. The Cache Evictor, implemented with the Terracotta Integration Module tim-map-evictor, provides a number of advantages over more complex solutions:

Simple: API is easy to understand and code against.

Standard: Data eviction is based on standard expiration metrics.

Lightweight: Implementation does not hog resources.

Efficient: Optimized for a clustered environment to minimize faulting due to low locality of reference.

Fail-safe: Data can be evicted even if written by a failed node or after all nodes have been restarted.

Native: Designed for Terracotta to eliminate integration issues.

How to Implement and Configure

The Terracotta Cache Evictor

Requirements

The Terracotta distributed data cache requires JDK 1.5 or greater.

Characteristics

Notable characteristics include:

A cache-wide Time To Live (TTL) value can be set. The TTL determines the maximum amount of time an object can remain in the cache before becoming eligible for eviction, regardless of other conditions such as use.

A cache-wide Time To Idle (TTI) value can be set. The TTI determines the maximum amount of time an object can remain idle in the cache before becoming eligible for eviction. TTI is reset each time the object is used.

Each cache element receives an internal timestamp used against the cache-wide TTL and TTI.

A Simple Cache with Terracotta Cache Evictor

Clustered applications with a system of record (SOR) on the backend can benefit from a distributed cache that manages certain data in memory while reducing costly application-SOR interactions. However, using a cache can introduce increased complexity to software development, integration, operation, and maintenance.

The Terracotta Cache Evictor includes a distributed-map that can be used as a simple distributed cache. This cache uses the Terracotta Cache Evictor, incorporating all of its benefits. It also takes both established and innovative approaches to the caching model, solving performance and complexity issues by:

obviate SOR commits for data with a limited lifetime;

making cached application data available in-memory across a cluster of application servers;

offering standard methods for working with cache elements and performing cache-wide operations;

incorporating concurrency for readers and writers;

utilizing a flexible map implementation to adapt to more applications;

minimizing inter-node faulting to speed data operations.

Structure and Characteristics

The Terracotta distributed cache is an interface incorporating a distributed map with standard map operations:

Terracotta Cache Evictor in a Reference Application

The [Examinator reference application] uses the Terracotta Cache Evictor to handle pending user registrations. This type of data has a "medium-term" lifetime which needs to be persisted long enough to give prospective registrants a chance to verify their registrations. If a registration isn't verified by the time TTL is reached, it can be evicted from the cache. Only if the registration is verified is it written to the database.

The combination of Terracotta and the Terracotta Cache Evictor gives Examinator the following advantages:

The simple Terracotta Cache Evictor's API makes it easy to integrate with Examinator and to maintain and troubleshoot.

Medium-term data is not written to the database unnecessarily, improving application performance.

Terracotta persists the pending registrations so they can survive node failure.

Terracotta clusters (shares) the pending registration data so that any node can handle validation.